Semantic smoothing of document models for agglomerative clustering
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Intelligent steganalytic system: application on natural language environment
WSEAS Transactions on Systems and Control
A bayesian approach to classify conference papers
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
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Text classification usually assumed a word-based document representation. In this paper, we propose a new approach to integrate compound terms in Bayesian text classification. Compound terms are used as complementary features to single words. An acute problem is to consider their dependence with the component words. In this paper, we propose to use smoothing techniques to combine both compound term and word representations. Experiments have been conducted on two corpora. Our results show that this approach can slightly but steadily improve the classification performance on both test corpora.